I have a table input of data on cars. Roughly 73 observations with 11 variables. I was tasked to find the mean of MPG by gear_ratio. This is the output I receive after completing an aggregate function.

dfdata=data.frame(cars10)
aggregate(x= dfdata$mpg, by=list(dfdata$gear_ratio), FUN=mean)

Next I would like to group and graph the following means by a range of Gear_ratio. The ranges need to be a) 2.0-2.5 b) 2.5 to 3.0 c)3.0-3.5 and d)3.5-4.0. I'd like to change colors for each group as well.

*Wasn't sure if there was a way to group by range in the initial aggregate function I created to find the mean in the first place.

CodePudding user response：

This is what I think the OP is asking for. I'm using mtcars data for demonstration and using the wt variable instead of gears as it has values similar to your gear_ratio:

library(dplyr) # for select and case_when and group_by
data = mtcars%>%
  select(wt, mpg)%>%
  mutate(wt_group =  case_when(wt >4 ~ ">4",  # form the groups based on ranges
                              wt >=3.5 ~ "3.5-4", # case_when will read this in order, so no need to do conditional statements such as wt >=3.0 but <3.5
                              wt >=3.0 ~ "3.0-3.5",
                              wt >=2.5 ~ "2.5-3.0",
                              wt >=2.0 ~ "2.0-2.5",
                              wt < 2.0 ~ "<2.0"))%>%
  group_by(wt_group)%>%
  summarise(mean_mpg = mean(mpg) )
> head(data)
# A tibble: 6 x 2
  wt_group mean_mpg
  <chr>       <dbl>
1 <2.0         30.5
2 >4           13.0
3 2.0-2.5      25.7
4 2.5-3.0      20.8
5 3.0-3.5      19.3
6 3.5-4        15.7

Then for the plot :

library(ggplot2)
plot = ggplot(data, aes(x= wt_group, y = mean_mpg , fill = wt_group)) 
  geom_col()
plot

Please edit the question and I can update answer if this doesn't give you what you need.

CodePudding user response：

library(dplyr)

df %>% 
  mutate(gear_group = cut(Gear_ratio,seq(0,4,.5)))

# A tibble: 15 x 3
   Gear_ratio Mean_MPG gear_group
        <dbl>    <dbl> <fct>     
 1       2.19     14   (2,2.5]   
 2       2.24     21   (2,2.5]   
 3       2.26     25   (2,2.5]   
 4       2.28     17   (2,2.5]   
 5       2.47     21   (2,2.5]   
 6       2.53     17   (2.5,3]   
 7       2.56     17.5 (2.5,3]   
 8       2.73     21.3 (2.5,3]   
 9       2.75     20.1 (2.5,3]   
10       2.87     34   (2.5,3]   
11       3.05     23.6 (3,3.5]   
12       3.15     17   (3,3.5]   
13       3.5      23   (3,3.5]   
14       3.87     18   (3.5,4]   
15       3.9      30.3 (3.5,4]